Demonstrating climate change in Prince Edward Island – A procedure using climate normals and weather data suitable for classroom use
Bibliographic record
Abstract
A simple method to assess climate warming is described, which is suitable for post-secondary classes in environmental sciences. This method is based on climate normals and subsequent weather data, and is demonstrated using Government of Canada archived climate/weather data from sites in Prince Edward Island including Charlottetown Airport, Alliston and New Glasgow. The method uses a simple statistical analysis based on one or two sample Student’s t-tests as well as scatter plots and linear regression to highlight the direction and magnitude of changes. Statistically significant increases of annual average temperature of 0.7°C to 1.3°C were calculated for the period after the end of the 1961-1990 climate normals for Alliston and Charlottetown, and a 0.9°C change was demonstrated for New Glasgow after the 1971-2000 climate normals. These values suggest a recent rate of change three times greater than a previous estimate of up to 0.9°C per century for the Gulf of St. Lawrence region, with a major temperature increase occurring in the late 1990s. Changes were most pronounced during September and December, and two sites showed a significant increase in continuous frost-free days during the growing season, as well as a decline in the number of days with frost during spring and fall. Keywords: Climate change, climate normals, Prince Edward Island, weather
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".